Literature DB >> 32236847

Delta-radiomics increases multicentre reproducibility: a phantom study.

Valerio Nardone1, Alfonso Reginelli2, Cesare Guida1, Maria Paola Belfiore3, Michelangelo Biondi4, Maria Mormile1, Fabrizio Banci Buonamici4, Eugenio Di Giorgio5, Marco Spadafora5, Paolo Tini6, Roberta Grassi3, Luigi Pirtoli6, Pierpaolo Correale7, Salvatore Cappabianca3, Roberto Grassi3.   

Abstract

Texture analysis (TA) can provide quantitative features from medical imaging that can be correlated to clinical endpoints. The challenges relevant to robustness of radiomics features have been analyzed by many researchers, as it seems to be influenced by acquisition and reconstruction protocols. Delta-texture analysis (D-TA), conversely, consist in the analysis of TA feature variations at different acquisition times, usually before and after a therapy. Aim of this study was to investigate the influence of different CT scanners and acquisition parameters in the robustness of TA and D-TA. We scanned a commercial phantom (CIRS model 467, Gammex, Middleton, WI, USA), that is used for the calibration of electron density, two times by varying the disposition of plugs, using three different scanners. After the segmentation, we extracted TA features with LifeX and calculated TA features and D-TA features, defined as the variation of each TA parameters extracted from the same position by varying the plugs with the formula (Y-X)/X. The robustness of TA and D-TA features were then tested with intraclass coefficient correlation (ICC) analysis. The reliability of TA parameters across different scans, with different acquisition parameters and ROI positions has shown poor reliability in 12/37 and moderate reliability in the remaining 25/37, with no parameters showing good reliability. The reliability of D-TA, conversely, showed poor reliability in 10/37 parameters, moderate reliability in 10/37 parameters, and good reliability in 17/37 parameters. The comparison between TA and D-TA ICCs showed a significant difference for the whole group of parameters (p:0.004) and for the subclasses of GLCM parameters (p:0.033), whereas for the other subclasses of matrices (GLRLM, NGLDM, GLZLM, Histogram), the difference was not significant. D-TA features seem to be more robust than TA features. These findings reinforce the potentiality for using D-TA features for early assessment of treatment response and for developing tailored therapies. More work is needed in a clinical setting to confirm the results of the present study.

Entities:  

Keywords:  Imaging; Lung cancer; Radiomics; Texture analysis

Year:  2020        PMID: 32236847     DOI: 10.1007/s12032-020-01359-9

Source DB:  PubMed          Journal:  Med Oncol        ISSN: 1357-0560            Impact factor:   3.064


  40 in total

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Authors:  Sarah A Mattonen; Shyama Tetar; David A Palma; Alexander V Louie; Suresh Senan; Aaron D Ward
Journal:  J Med Imaging (Bellingham)       Date:  2015-11-12

2.  Transthoracic computed tomography-guided lung biopsy in the new era of personalized medicine.

Authors:  Umberto Russo; Vittorio Sabatino; Rita Nizzoli; Marcello Tiseo; Salvatore Cappabianca; Alfonso Reginelli; Gianpaolo Carrafiello; Luca Brunese; Massimo De Filippo
Journal:  Future Oncol       Date:  2019-03-18       Impact factor: 3.404

3.  Texture Analysis on [18F]FDG PET/CT in Non-Small-Cell Lung Cancer: Correlations Between PET Features, CT Features, and Histological Types.

Authors:  Francesco Bianconi; Isabella Palumbo; Mario Luca Fravolini; Rita Chiari; Matteo Minestrini; Luca Brunese; Barbara Palumbo
Journal:  Mol Imaging Biol       Date:  2019-12       Impact factor: 3.488

4.  Bone texture analysis using CT-simulation scans to individuate risk parameters for radiation-induced insufficiency fractures.

Authors:  V Nardone; P Tini; S F Carbone; A Grassi; M Biondi; L Sebaste; T Carfagno; E Vanzi; G De Otto; G Battaglia; G Rubino; P Pastina; G Belmonte; L N Mazzoni; F Banci Buonamici; M A Mazzei; L Pirtoli
Journal:  Osteoporos Int       Date:  2017-02-27       Impact factor: 4.507

5.  Measuring Computed Tomography Scanner Variability of Radiomics Features.

Authors:  Dennis Mackin; Xenia Fave; Lifei Zhang; David Fried; Jinzhong Yang; Brian Taylor; Edgardo Rodriguez-Rivera; Cristina Dodge; Aaron Kyle Jones; Laurence Court
Journal:  Invest Radiol       Date:  2015-11       Impact factor: 6.016

6.  Test-retest reproducibility analysis of lung CT image features.

Authors:  Yoganand Balagurunathan; Virendra Kumar; Yuhua Gu; Jongphil Kim; Hua Wang; Ying Liu; Dmitry B Goldgof; Lawrence O Hall; Rene Korn; Binsheng Zhao; Lawrence H Schwartz; Satrajit Basu; Steven Eschrich; Robert A Gatenby; Robert J Gillies
Journal:  J Digit Imaging       Date:  2014-12       Impact factor: 4.056

7.  Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer.

Authors:  Sarah A Mattonen; David A Palma; Cornelis J A Haasbeek; Suresh Senan; Aaron D Ward
Journal:  Med Phys       Date:  2014-03       Impact factor: 4.071

8.  Quantifying tumour heterogeneity with CT.

Authors:  Balaji Ganeshan; Kenneth A Miles
Journal:  Cancer Imaging       Date:  2013-03-26       Impact factor: 3.909

9.  Reproducibility of radiomics for deciphering tumor phenotype with imaging.

Authors:  Binsheng Zhao; Yongqiang Tan; Wei-Yann Tsai; Jing Qi; Chuanmiao Xie; Lin Lu; Lawrence H Schwartz
Journal:  Sci Rep       Date:  2016-03-24       Impact factor: 4.379

10.  Delta radiomics for rectal cancer response prediction with hybrid 0.35 T magnetic resonance-guided radiotherapy (MRgRT): a hypothesis-generating study for an innovative personalized medicine approach.

Authors:  Luca Boldrini; Davide Cusumano; Giuditta Chiloiro; Calogero Casà; Carlotta Masciocchi; Jacopo Lenkowicz; Francesco Cellini; Nicola Dinapoli; Luigi Azario; Stefania Teodoli; Maria Antonietta Gambacorta; Marco De Spirito; Vincenzo Valentini
Journal:  Radiol Med       Date:  2018-10-29       Impact factor: 3.469

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  22 in total

1.  Delta radiomics: a systematic review.

Authors:  Valerio Nardone; Alfonso Reginelli; Roberta Grassi; Luca Boldrini; Giovanna Vacca; Emma D'Ippolito; Salvatore Annunziata; Alessandra Farchione; Maria Paola Belfiore; Isacco Desideri; Salvatore Cappabianca
Journal:  Radiol Med       Date:  2021-12-04       Impact factor: 3.469

2.  Prognostic analysis and risk stratification of lung adenocarcinoma undergoing EGFR-TKI therapy with time-serial CT-based radiomics signature.

Authors:  Xiaobo Zhang; Bingfeng Lu; Xinguan Yang; Dong Lan; Shushen Lin; Zhipeng Zhou; Kai Li; Dong Deng; Peng Peng; Zisan Zeng; Liling Long
Journal:  Eur Radiol       Date:  2022-09-27       Impact factor: 7.034

3.  Ability of Delta Radiomics to Predict a Complete Pathological Response in Patients with Loco-Regional Rectal Cancer Addressed to Neoadjuvant Chemo-Radiation and Surgery.

Authors:  Valerio Nardone; Alfonso Reginelli; Roberta Grassi; Giovanna Vacca; Giuliana Giacobbe; Antonio Angrisani; Alfredo Clemente; Ginevra Danti; Pierpaolo Correale; Salvatore Francesco Carbone; Luigi Pirtoli; Lorenzo Bianchi; Angelo Vanzulli; Cesare Guida; Roberto Grassi; Salvatore Cappabianca
Journal:  Cancers (Basel)       Date:  2022-06-18       Impact factor: 6.575

Review 4.  Rectal MRI radiomics for predicting pathological complete response: Where we are.

Authors:  Joao Miranda; Gary Xia Vern Tan; Maria Clara Fernandes; Onur Yildirim; John A Sims; Jose de Arimateia Batista Araujo-Filho; Felipe Augusto de M Machado; Antonildes N Assuncao-Jr; Cesar Higa Nomura; Natally Horvat
Journal:  Clin Imaging       Date:  2021-11-16       Impact factor: 2.420

Review 5.  The Role of Radiomics in Lung Cancer: From Screening to Treatment and Follow-Up.

Authors:  Radouane El Ayachy; Nicolas Giraud; Paul Giraud; Catherine Durdux; Philippe Giraud; Anita Burgun; Jean Emmanuel Bibault
Journal:  Front Oncol       Date:  2021-05-05       Impact factor: 6.244

Review 6.  Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging.

Authors:  Domenico Albano; Federico Bruno; Andrea Agostini; Salvatore Alessio Angileri; Massimo Benenati; Giulia Bicchierai; Michaela Cellina; Vito Chianca; Diletta Cozzi; Ginevra Danti; Federica De Muzio; Letizia Di Meglio; Francesco Gentili; Giuliana Giacobbe; Giulia Grazzini; Irene Grazzini; Pasquale Guerriero; Carmelo Messina; Giuseppe Micci; Pierpaolo Palumbo; Maria Paola Rocco; Roberto Grassi; Vittorio Miele; Antonio Barile
Journal:  Jpn J Radiol       Date:  2021-12-24       Impact factor: 2.374

7.  Radiomics-Based Outcome Prediction for Pancreatic Cancer Following Stereotactic Body Radiotherapy.

Authors:  Elsa Parr; Qian Du; Chi Zhang; Chi Lin; Ahsan Kamal; Josiah McAlister; Xiaoying Liang; Kyle Bavitz; Gerard Rux; Michael Hollingsworth; Michael Baine; Dandan Zheng
Journal:  Cancers (Basel)       Date:  2020-04-24       Impact factor: 6.639

Review 8.  Diagnostic evaluation and ablation treatments assessment in hepatocellular carcinoma.

Authors:  Vincenza Granata; Roberta Grassi; Roberta Fusco; Andrea Belli; Carmen Cutolo; Silvia Pradella; Giulia Grazzini; Michelearcangelo La Porta; Maria Chiara Brunese; Federica De Muzio; Alessandro Ottaiano; Antonio Avallone; Francesco Izzo; Antonella Petrillo
Journal:  Infect Agent Cancer       Date:  2021-07-19       Impact factor: 2.965

9.  Delta-radiomics and response to neoadjuvant treatment in locally advanced gastric cancer-a multicenter study of GIRCG (Italian Research Group for Gastric Cancer).

Authors:  Maria Antonietta Mazzei; Letizia Di Giacomo; Giulio Bagnacci; Valerio Nardone; Francesco Gentili; Gabriele Lucii; Paolo Tini; Daniele Marrelli; Paolo Morgagni; Gianni Mura; Gian Luca Baiocchi; Frida Pittiani; Luca Volterrani; Franco Roviello
Journal:  Quant Imaging Med Surg       Date:  2021-06

10.  COVID-19 pneumonia: computer-aided quantification of healthy lung parenchyma, emphysema, ground glass and consolidation on chest computed tomography (CT).

Authors:  Roberto Grassi; Maria Paola Belfiore; Alessandro Montanelli; Gianluigi Patelli; Fabrizio Urraro; Giuliana Giacobbe; Roberta Fusco; Vincenza Granata; Antonella Petrillo; Palmino Sacco; Maria Antonietta Mazzei; Beatrice Feragalli; Alfonso Reginelli; Salvatore Cappabianca
Journal:  Radiol Med       Date:  2020-11-18       Impact factor: 3.469

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